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Predictive Modeling Shapes Student Admissions

Members of the Class of 2019 will begin to tackle their UI academic lives in August, but the office responsible for bringing that class to campus took on its own challenges many months before, including successfully meeting ambitious enrollment goals set by then-President Sally Mason. During that time, the Office of Admissions also was quietly re-inventing itself as an enterprise informed by data to better meet future enrollment goals.

With the December 2014 arrival of Associate Vice President for Enrollment Management Brent Gage, PhD, the Offices of Admissions and Financial Aid have been combined into one enrollment management unit in which data analytics will inform both strategic recruitment as well as the strategic use of financial aid scholarships. Staff members in both offices have begun to lay the foundation for using data analytics to shape future incoming classes.

“The level of sophistication being used at the University of Iowa to build our incoming class represents a trend that will likely become the future of how college admissions will successfully function,” Gage says. “We are working diligently to become a learning organization that evolves to continually meet the needs of our students and achieve institutional goals.”

For Admissions, this has meant developing sophisticated predictive models to identify students most likely to enroll, and with a high likelihood of meeting the University’s academic challenges.

For Financial Aid, this has meant re-working scholarship criteria to attract desired students in the most cost-effective way. Tapping large-scale data and leveraging predictive modeling will enable members of Gage’s staff to tailor their outreach to students who are most interested in the opportunities offered by the University and equally important, to focus on students who are most likely to be academically successful at the University.

The process of shaping and attracting a new class begins months—even years—before students actually arrive on campus. In describing a future class that will be the best “fit,” UI administrators consider a variety of factors, including student demographics, academic achievement, class size, and University resource capacity.

Big data analytics is making that process more streamlined and definitive. The process of leveraging big data to secure “best fit” students also considers the viewpoint of prospective students themselves.

“We want to better understand what’s important to high school students—their preferences, needs, and interests—and then let them know what Iowa can offer,” Director of Enrollment Management Data Analytics Michael Hovland, PhD, says. “We’re moving away from the ‘one-size-fits-all’ approach, which isn’t terribly efficient or effective in getting the kinds of students we want.”